The present invention, in some embodiments thereof, relates to neurophysiology and, more particularly, but not exclusively, to method and system for analyzing data using spatiotemporal parcellation.
Little is known about the mechanisms that allow the brain to selectively improve the neural representations of behaviorally important stimuli while ignoring irrelevant stimuli. The brain is a complex structure of nerve cells that produce signals called action potentials. These action potentials move from one cell to another across a gap called the synapse. These potentials summate in the cortex and extend through the coverings of the brain to the scalp, where they can be measured using appropriate electrodes. Rhythmical measured activity represents postsynaptic cortical neuronal potentials which are synchronized by the complex interaction of large populations of cortical cells.
Behavioral functions are based upon flow among various functional regions in the brain, involving specific spatiotemporal flow patterns. A specific spatiotemporal pattern underlying a certain behavioral function is composed of functional brain regions, which are often active for at least several tens of milliseconds and more. The flow of activity among those regions is often synchronization-based.
Known in the art are methods that identify discrete participating regions for the purpose of relating behavioral functions to their underlying localized brain activities. Other techniques employ analysis of the flow from one region to another.
U.S. Pat. No. 6,792,304 discloses a method and a system for mass communication assessment. A cognitive task is transmitted from a central control site to a plurality of remote test sites via Internet. The brain response of the subjects at the remote sites in response to the task is recorded and transmitted back to the central control site via the Internet. The central control site then computes the variations in the brain activities for the subjects at each of the selected sites.
U.S. Published Application No. 20040059241 discloses a method for classifying and treating physiologic brain imbalances. Neurophysiologic techniques are used for obtaining a set of analytic brain signals from a subject, and a set of digital parameters is determined from the signals. The digital parameters are quantitatively mapped to various therapy responsivity profiles. The signals and parameters for a subject are compared to aggregate neurophysiologic information contained in databases relating to asymptomatic and symptomatic reference populations, and the comparison is used for making treatment recommendations. Treatment response patterns are correlated as a dependent variable to provide a connection to successful outcomes for clinical treatment of afflicted subjects.
International Publication No. WO 2007/138579, the contents of which are hereby incorporated by reference, describes a method for establishing a knowledge base of neuropsychological flow patterns. Signals from multiple research groups for a particular behavioral process are obtained, and sources of activity participating in the particular behavioral functions are localized. Thereafter, sets of patterns of brain activity are identified, and neuropsychological analysis is employed for analyzing the localized sources and the identified patterns. The analysis includes identification and ranking of possible pathways. A set of flow patterns is then created and used as a knowledge base. The knowledge base is then used as a constraint for reducing the number of ranked pathways.
International Publication Nos. WO 2009/069134, WO 2009/069135 and WO 2009/069136, the contents of which are hereby incorporated by reference, describe a technique in which neurophysiological data are collected before and after the subject has performed a task and/or action that forms a stimulus. The stimulus is used for defining features in the data, and the data are decomposed according to the defined features. Thereafter, the features are analyzed to determine one or more patterns in the data. The decomposition can employ clustering for locating one or more important features in the data, wherein a collection of clusters forms an activity network. The data patterns can be analyzed for defining a neural model which can be used for simulating the effect of a particular pathology and/or treatment on the brain.
International Publication Nos. WO 2011/086563, the contents of which are hereby incorporated by reference, discloses analysis of neurophysiological data, which includes identifying activity-related features in the data, constructing a brain network activity (BNA) pattern having a plurality of nodes, each representing a feature of the activity-related features, and assigning a connectivity weight to each pair of nodes in the BNA pattern.
Additional background art includes U.S. Published Application No. 20050177058, which discloses a system in which EEG readings from more than one subject at the same or different locations are collected, analyzed and compared, when they are exposed to a common set of stimuli. The compatibility of the subjects is studied using their EEG readings, and concealed information is discovered or verified from.